wind_pypcd

=======

安装方式

稳定版本

pip3 install wind-pypcd

开发模式

pip3 install -v -e .   

usage

from pypcd import pypcd
# 读取ros的pointcloud2消息
pc = pypcd.PointCloud.from_msg(data)
x = pc.pc_data['x']
y = pc.pc_data['y']
z = pc.pc_data['z']

# 读取pcd文件
pc = pypcd.PointCloud.from_path('foo.pcd')
x = pc.pc_data['x']
y = pc.pc_data['y']
z = pc.pc_data['z']

# 读取bin文件
pc = pypcd.PointCloud.from_bin("foo.bin", format="xyzi")

# 读取 numpy array
pc = pypcd.PointCloud.from_array_without_dtype(arr, format="xyzi")

# 保存pcd
pc = pypcd.PointCloud.from_msg(msg)
pc.save_pcd('foo.pcd', compression='binary_compressed')

# 保存bin
pc.save_bin("foo.bin", "xyzi")

本库的特点

• 基于python3
• 支持ros的pointcloud2消息
• 目前还在维护,但是不会频繁，大概率是仅解决一些依赖库的问题
• 可通过pip安装

创建本库的原因

• 在python下一直没有对pcd的很好的支持库，于是pypcd作者基于python2实现了一个，但python2已经不再维护，所以klintan基于python3重新实现了一个,本仓库便是fork自此pypcd
• 原仓库太久没有维护，导致很多基于numpy的方法已经失效，本仓库在此基础上进行了修复
• 无法通过pip安装，作为依赖使用起来不方便，所以本仓库托管在了pypi上，可以通过pip安装，但是因为原仓库的名字已经被占用，所以本仓库的名字为wind_pypcd

Old README

What?

Pure Python module to read and write point clouds stored in the PCD file format, used by the Point Cloud Library.

Why?

You want to mess around with your point cloud data without writing C++ and waiting hours for the template-heavy PCL code to compile.

You tried to get some of the Python bindings for PCL to compile and just gave up.

How does it work?

It parses the PCD header and loads the data (whether in ascii, binary or binary_compressed format) as a Numpy structured array. It creates an instance of the PointCloud class, containing the point cloud data as pc_data, and some convenience functions for I/O and metadata access.

Example

import pypcd
# also can read from file handles.
pc = pypcd.PointCloud.from_path('foo.pcd')
# pc.pc_data has the data as a structured array
# pc.fields, pc.count, etc have the metadata

# center the x field
pc.pc_data['x'] -= pc.pc_data['x'].mean()

# save as binary compressed
pc.save_pcd('bar.pcd', compression='binary_compressed')

Is it beautiful, production-ready code?

No.

What else can it do?

There's a bunch of functionality accumulated over time, much of it hackish and untested. In no particular order,

• Supports ascii, binary and binary_compressed data. The latter requires the lzf module.
• Decode and encode RGB into a single float32 number. If you don't know what I'm talking about consider yourself lucky.
• Point clouds from pandas dataframes.
• Convert to and from ROS PointCloud2 messages. Requires the ROS sensor_msgs package with Python bindings installed. This functionality uses code developed by Jon Binney under the BSD license, included as numpy_pc2.py.

What can't it do?

There's no synchronization between the metadata fields in PointCloud and the data in pc_data. If you change the shape of pc_data without updating the metadata fields you'll run into trouble.

I've only used it for unorganized point cloud data (in PCD conventions, height=1), not organized data like what you get from RGBD.

While padding and fields with count larger than 1 seem to work, this is a somewhat ad-hoc aspect of the PCD format, so be careful. If you want to be safe, you're probably better off using neither -- just name each component of your field something like FIELD_00, FIELD_01, etc.

It's slow

Try using binary or binary_compressed; using ASCII is slow and takes up a lot of space, not to mention possibly inaccurate if you're not careful with how you format your floats.

I found a bug / I added a feature / I made your code cleaner

Thanks! Please submit a pull request.

I want to congratulate you / insult you

My email is dimatura@cmu.edu.

Copyright (C) 2015 Daniel Maturana